From Concepts to Cutting-Edge Data Engineering
Learn how to take data and AI concepts from concept to prototype and to production-ready application. Acquire the skills to develop and run Data and AI solutions at an enterprise-scale with ease! Take part in a specific training or advance through the entire journey. Learn how to build secure data platforms and reliable AI applications that are engineered for scale.
The Learning Journey for Data Engineers
How do you become a data engineering expert? Start here! We’ve put together a carefully crafted learning journey for data engineers. Knowing engineers love to figure things out on their own, we packed the program with opportunities to learn, hands-on, by solving real-life situations. Plus, there’s plenty of practical philosophy, too.
We’ll teach you how to leverage Docker to ease your deployments and navigate code written by data scientists ( Advanced Python and Data Science in Production). You will learn to use Apache Airflow, Apache Spark, and Kafka like a forklift to move data around. And we won’t shy away from proven technologies either, like ElasticSearch. We also remain on the cutting edge with others, like Apache Flink.
Download Data Engineering Training Guide
Download the Xebia Guide for a complete overview of available training sessions and Data Engineering learning journeys
Junior Data Engineer
Learning Goals for a Junior Data Engineers
- Writes correct and clean code with guidance
- Participates in the technical design of features with guidance
- Knows how to integrate CI/CD concepts into their daily coding
- Able to create simple pipelines without guidance
- Knows how containerization works, and what it simplifies
- Can write and push containers
- Public dbt Learn Training / 2-days – Public
Build models to shape your data from raw data to transformed data
- Python for Data Engineers / 2-days – Public & In-Company
This 2-days Xebia training will provide you with the necessary tools to help you turn your code simple, beautiful and truly pythonic.
- Data Processing at Scale / 2-days – In-Company
This training goes deep down into one of the most popular and scalable tools in the market for large-data transformation: Apache Spark!
- Docker & Kubernetes / 3-days – In-Company
This training takes you through everything you need to know to package applications into containers and run them on Kubernetes
+ Professional Scala Development / 2-days – Public & In-Company
Medior Data Engineer
Learning Goals for a Medior Data Engineers
- Understands and makes well-reasoned design decisions and trade-offs in their area
- Able to quickly get familiar with larger codebases
- Able to create complex pipelines without guidance
- Apache Airflow/ 1-days – Public & In-Company
This 1-day Xebia training teaches you the internals, terminology, and best practices of writing DAGs. Plus hands-on experience in writing and maintaining data pipelines.
- Optimizing Apache Spark & Tuning Best Practices / 2-days – In-Company
Building up from the experience we built at the largest Apache Spark users in the world, we give you an in-depth overview of the do’s and don’ts of one of the most popular analytics engines out there.
- Create Data Data Science Products / 2-days – In-Company
In this course you’ll be introduced to how to efficiently productionize data science models.
+ Concurrency in Scala / 2 days – Public & In-Company
Senior Data Engineer
Learning Goals for a Senior Data Engineers
- Go-to expert in one area; understands the broad architecture of the entire system
- Provides technical advice and weighs in on technical decisions that impact other teams or the company at large
Cloud Data Engineer
Learning Goals for a Cloud Data Engineers
- Go-to expert for data engineering in the cloud; understands the services that simplifies the architecture of the entire landscape
- Provides technical advice and weighs in on technical decisions that impact the cloud infrastructure at the company level
- Big Data on AWS Training / 1-day – In-Company
In this training, you will learn about cloud-based Big Data solutions such as Amazon EMR, Amazon Redshift, Amazon Kinesis, and the rest of the AWS Big Data platform.
- Google Cloud Platform Fundamentals: Big Data & Machine Learning Training / 1-day – Public & In-CompanyThis 1-day Foundation level training is all you need to get started with Big Data and Machine Learning on GCP.
- Data Engineering on Google Cloud Platform Training / 4-days – Public & In-Company
This course is part of Google’s Data Engineering track that leads to the Professional Data Engineer certificate.
The training gave me a lot of grip and insights on the subject. How to use pandas, cleaning up your data, and plotting data were the most interesting parts for me.
aThe training did not only provide knowledge about pandas, scikit-learn, but also about the way to think as a data scientist.
The training really starts from scratch, which is a great thing for beginners. The training covers a large range of topics in R, ending with a very interesting section on modelling
I liked every aspect of the training and would like to thank the trainers. They did an excellent job in explaining how to use Spark for data science. This is now the fourth training from Xebia that I followed, they were all great, but this was the best one so far.
Develop the skills of your organization
Find the right courses to grow your team’s Data & AI skills, or design learning journeys at scale to empower your entire organization.
Data Pipelines with Apache Airflow
Yes, we’re book authors too.
Our experienced data engineers Bas Harenslak and Julian de Ruiter explain how to use Apache Airflow to create efficient and automated pipelines. They use their consulting experience from companies like Heineken, Unilever and Booking.com to present relevant use cases and applications.
You will find the following content in the book:
- Framework foundation and best practices
- Airflow’s execution and dependency system
- Testing Airflow DAGs
- Running Airflow in production